Biomarker-Based Lung Cancer Screening Eligibility: Implementation Considerations

Lung cancer remains to be a global public health priority with approximately 1.8 million deaths annually worldwide (1). Low-dose computed tomography (LDCT) screening was shown to reduce lung cancer mortality by 20% to 40%, depending on sex and follow-up time (2, 3). Despite the recently relaxed criteria by the United States Preventive Services Task Force (USPSTF; ref. 4), approximately 30% to 40% of lung cancer occur in those who do not meet the criteria, depending on the study populations (5). In the recent International Lung Screening Trial, it was demonstrated that individual risk–based eligibility can improve lung cancer efficiency (6).

In this issue, Jacobsen and colleagues reported an improved specificity and lower screening burden when adding aryl-hydrocarbon receptor repressor (AHRR) hypomethylation as part of the CT screening eligibility assessment based on the Copenhagen City Heart cohort study, but did not improve sensitivity or positive predictive value (7). Although the associations between leukocyte AHRR hypomethylation, cumulative tobacco smoking, and lung cancer risk have been previously reported (8, 9), this is the first study that systematically assessed the implication of this blood-based biomarker on lung cancer CT screening eligibility (7).

Given that the AHRR methylation was mainly a marker of cumulative tobacco exposure history, it was not unexpected that it improved specificity but not sensitivity. The implication is that this biomarker may help to lower the screening burden by capturing those who are at highest risks (via refining internal tobacco exposures vs. self-reported smoking history), but might not be able to identify those who are currently not eligible for CT screening, such as light smokers, long-term former smokers, and high-risk never smokers in specific populations.

In addition to AHRR methylation, several promising biomarker classes, which can be obtained either noninvasively or through peripheral blood, have been suggested to improve lung cancer risk stratification for LDCT screening eligibility, including circulating protein markers, autoantibody, circulating cell-free methylome, microRNA, exhaled breath, and more (10). Notably, several randomized control trials were initiated to test whether some of these biomarker classes would affect the CT screening efficiency, such as the Early Diagnosis of Lung Cancer Scotland trial (11), and the BioMILD trial in Italy (12). While at various stages of validation, the emergence of promising biomarkers for risk stratification begs the question of how these scientific advancements can be eventually translated to the actual implementation.

The introduction of biomarker-based eligibility tests in the lung cancer screening pathway holds promises as well as risks. The validation and assessment process of early detection biomarkers has been previously described (13). However even after a biomarker is well validated in multiple large prospective cohorts, there is still a long road ahead before it can be feasibly deployed in the population setting. One of the first steps is to demonstrate how the biomarker would improve upon the existing criteria, which was the focus of Jacobsen and colleagues. The following sections outline the considerations specifically related to implementations after validation and clinical utility assessment. Possible mitigation strategies for each of these considerations are summarized in Fig. 1.

The cost-effectiveness of the proposed biomarker is front and center as to how justifiable and feasible the biomarker test can be implemented for screening eligibility, which undoubtedly would vary substantially by the biomarker performance and the health care setting. Other factors that would affect its cost-effectiveness include whether a biomarker could inform optimal time to initiate screening, or optimal screening intervals. A recent microsimulation model was conducted for noninvasive biomarkers applied after LDCT screening at the time of nodule detection (14). No formal cost-effectiveness analysis has been reported to date for pre-LDCT screening biomarkers, although it is an active research area of the Cancer Intervention and Surveillance Modeling Network Lung cancer group (CISNET-Lung, https://cisnet.cancer.gov/lung/).

Racial disparity and sex-based differences associated with the 2013 USPSTF criteria were well documented; For example, African Americans have higher lung cancer incidence but with lower smoking intensity, and the criteria sensitivity is lower in women (15–17). The recently modified 2021 USPSTF criteria were shown to reduce some of these disparities by lowering the threshold of smoking pack-years (5). In general, it was shown that the eligibility assessment based on risk prediction models helps to address these disparities (16, 18, 19), and biomarker is a tool to help achieve a more accurate individual risk assessment. While contributing to individual risk–based assessment, the biomarker for CT screening eligibility needs to have proven generalizability across different racial groups in the target population. A common limitation of most of the emerging biomarkers is the lack of transferability across different populations. In the case of AHRR methylation, although previous studies have shown associations with tobacco smoking in multiple racial groups (9), the study of Jacobsen and colleagues included a population of predominately European ancestry and thus a comprehensive assessment of the impact on screening eligibility in different racial backgrounds would be warranted. Since the optimal biomarker panels may vary by key risk factors (e.g., smoking status), a well-defined target population and representativeness of the study population are important to ensure implementation success.

One of the main obstacles of implementing a lung cancer screening program is the suboptimal uptake, which can be due to the social stigma of the disease, difficulties to determine the eligibility based on past smoking history, or lack of access to medical care, or insurance coverage. In the United States, where lung cancer CT screening has been implemented and covered by the Centers for Medicare & Medicaid Services, only less than 20% of eligible populations entered the screening program (20). In Canada, it was observed that having trained navigators, instead of physicians, to guide participants through the screening pathways helps to increase screening uptake and adherence (21). In the UK, the community-based approach with mobile units has been deployed to increase uptake (22). It would be important to assess how the addition of biomarker-based assessment would affect the screening behavior and uptake. Currently, there is no empirical data that shows how the implementation of a biomarker-based assessment would modify the screening behaviors. However, one of the main bottlenecks of the screening uptake is the inability to assess the eligibility, either by the physicians due to lack of support or reliable information, or by the participants themselves at the outset. Therefore, in theory, a simple biomarker test may solve these problems. In addition, a positive biomarker test may motivate participation, and subsequent risk reduction behavior (e.g., smoking cessation), while a negative biomarker test may spare those who are at low risk and in the hard-to-reach community (due to geographic or financial constraints) an unnecessary trip to a CT screening center. However, empirical data from feasibility studies and community engagement will be needed to understand how the introduction of biomarker tests in the screening pathway would change the screening uptake or adherence from both perspectives of the health care providers and the participants.

The issue of health care inequity has been documented in the context of lung cancer screening, where the populations that would benefit most from screening are also the ones that are underserved by the health care system, while communities with high social-economic status tend to be overrepresented in the screening participants (23). It is possible that the addition of the biomarker test in the screening pathway will impose additional hurdle to the population that already have limited access to the health care system and further widen the health care inequity. To minimize potential inequity, a population-based organized CT screening program is preferable instead of ad hoc or opportunistic screening, which can lead to more harm than benefit. In addition, related to an earlier point on racial differences, a biomarker that is developed predominately based on the European ancestry population would also further exacerbate the issues of inequity across racial groups. Similar consideration applies to sex-based differences. Therefore, the importance of the systematic approach based on guidelines defined by empirical data could not be overemphasized.

Regardless of the model of the laboratory setup (local or centralized), the biomarker test results would need to be communicated back to the participants in a timely and clear manner. There is a realistic risk of conflating a risk assessment biomarker with a diagnostic biomarker, which can lead to unwarranted negative consequences such as patient anxiety (24). Public education related to biomarker implications will need to be part of the implementation process. In addition, the health care professionals, including navigators in the screening pathways will need to undergo training for result interpretations and risk communications, and potentially identify the opportunity to promote risk reduction behavior. This is particularly relevant for lung cancer screening, as shared decision-making is an integral component of the screening pathway.

The center of the implementation success is the benefit–harm balance. Monitoring early adverse events such as unnecessary invasive procedures of benign nodules or participant anxiety, as well as longer-term outcome such as reduction in mortality and life-years gained will be the key (25). These assessments are periodically performed for the common screening criteria, and in general, risk model–based screening strategy is associated with better benefit–harm balance, but how the biomarker will shift this balance is yet to be seen (25). If the biomarker test can help to inform the optimal screening pathway such as time of initiation and intervals, it can potentially reduce the burden of health care utilization, follow-up procedures while maintaining the benefit of mortality reduction. On the other hand, issues related to any of the considerations described above can shift the balance in the other direction. These aspects will need to be evaluated on the basis of empirical data from prospective studies.

Lung cancer LDCT screening is a multistep pathway, not a one-time test. The process after LDCT screening related to nodule management is not included in this commentary, although it is an active research area and has its own set of considerations related to biomarkers, particularly in conjunction with quantitative imaging analysis. Overall, a holistic and organized approach integrated into the health care system, building on collaborations across multiple disciplines from biomedical discovery, population health, clinical expertise, and health services can help to ensure the implementation success.

No disclosures were reported.

The author thanks Drs. Stephen Lam and Ross E.G. Upshur for the helpful feedback. This work is supported by the CIHR Canada Research Chair to Rayjean J. Hung, and the NIH (U19 CA203654, INTEGRAL).